Examining the key determinants towards online pro-brand and anti-brand community citizenship behaviours. A two-stage approach

Publication Date14 May 2018
AuthorT.C. Wong,Mohamed Yacine Haddoud,Y.K. Kwok,Hongwei He
SubjectInformation & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems
Examining the key determinants
towards online pro-brand and
anti-brand community citizenship
A two-stage approach
T.C. Wong
DMEM, University of Strathclyde, Glasgow, UK
Mohamed Yacine Haddoud
Plymouth Business School, University of Plymouth, Plymouth, UK
Y.K. Kwok
University of Warwick, Coventry, UK, and
Hongwei He
Alliance Manchester Business School, University of Manchester, Manchester, UK
Purpose The purpose of this paper is to propose a research model to identify the key determinants and
examine their impact towards online pro-brand and anti-brand community citizenship behaviours (CCBs).
Design/methodology/approach A survey based on the research model is used to collect empirical data
from 260 and 200 members of online pro-brand communities (OBCs) and online anti-brand communities
(OABCs), respectively. A two-stage approach employing fuzzy-set qualitative comparative analysis and
artificial neural network (ANN) is first applied to uncover new observations.
Findings Moral identity and positive brand emotion (BE) are the two most influential factors driving both
online pro-brand and anti-brand CCBs. A higher level of internalisation might be required to exhibit online
anti-brand CCB as opposed to online pro-brand CCB. This contradicts the current understanding that
anti-brand behaviours are less morally restricted given the virtuality and anonymity of online communities.
OABC members may need to better justify themselves internally to overcome positive BE when exercising
anti-brand action. Also, brand identification, brand dis-identification and BE would be used to identify two
types of OABC members.
Research limitations/implications The effect of motives other than pro-social remains unclear on
online pro-brand and anti-brand CCBs.
Originality/value This is the firstpaper to develop two new dimensions which provide a more complete
definition of CCB. Also, some new observations are uncovered by comparing the effect of different key
determinants on onlinepro-brand CCB againstthat of onlineanti-brand CCB. Theresearch model can beused to
defineand improve member(or brand) engagementwhich wouldenhance the managementof OBCs and OABCs.
Keywords Social support, Socialidentity theory, Artificial neural network, Online community participation,
Fuzzy-set qualitative comparative analysis, Community citizenshipbehaviour
Paper type Research paper
1. Introduction
Online communities are widely known as web-based online services supporting and
facilitating information exchanges among community members (Malinen, 2015). One major
feature of online communities is the member engagement which can be seen as dependency
on members for generating or sharing online content, hence also known as member
participation. If the core focus of an online community is the brand itself, this community is
then known as online pro-brand community (OBC) where the online content is developed
around brand-related consumption experiences (Wirtz et al., 2013). By proper management
Industrial Management & Data
Vol. 118 No. 4, 2018
pp. 850-872
© Emerald PublishingLimited
DOI 10.1108/IMDS-07-2017-0313
Received 18 July 2017
Revised 29 September 2017
Accepted 7 November 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
of OBCs, firms can effectively respond to consumer feedback which would help drive
business improvement. For example, consumers can actively contribute to value co-creation
by offering new ideas or suggestions which would help uncover new business opportunities
(Liao et al., 2017). Opposing to OBC, online anti-brand community (OABC) aims to generate
or share anti-brand-related information to promote brand rejection behaviours such as
negative brand relationship and oppositional attitudinal loyalty (Dessart et al., 2016). In this
connection, it is vital to examine what factors affect the level of member engagement and
how such engagement can be realised in both communities. This can be termed as the
study of online community participation which has been seen as key to successful OBCs
and OABCs.
This paper is structured as follows. Section 2 shows the past work done and specifies the
research gaps. Section 3 describes the research model derived from the current literature.
Section 4 details the mechanism of the proposed two-stage approach with analysis
results reported in Section 5. Key findings are discussed in Section 6. Section 7 concludes the
whole paper.
2. Literature review
Online community participation can be studied from two main perspectives: personal and
social. From the personal perspective, most of the current studies have adopted various
theories or models to justify the individual behaviour towards online community
participation. For example, technology acceptance model has been used to examine how
ones attitude might determine ones adoption towards a new technology (i.e. participation in
OBCs) (Casaló et al., 2011; Agag and El-Masry, 2016). Elliot et al. (2013) examined the impact
of OBC quality on members intention to transact via members satisfaction and trust
towards OBC. Analysis suggested that quality was a key to affect both satisfaction and
trust which did have indirect effect on intention to transact via brand attitude and
stickiness. Some new insights were generated regarding the growing influence of new
measure (such as stickiness) as compared to traditional measure (such as trust). Other
theories such as theory of reasoned action (TRA) and trust theory have been applied
to explain the correlation between intention and action in the context of community
participation(Hsu and Lu, 2007; Kozinets et al., 2010).
From the social perspective, ones attitudes, intentions and actions towards online
community participation have been explained in consideration of various social theories or
models. For example, social exchange theory has been used to examine how members
exchange information via OBCs and what factors drive that participation (Benoit et al., 2016).
In their paper, factors specific to three parties (member, co-member and provider) were
examined. Analysis results suggested that co-members cooperation was deemed negatively
correlated with community participation which contracted the theory. Members role clarity
and enjoyment together with providers responsiveness were deemed significant to drive
community participation. Another commonly used theory, social identity theory, specifies
how ones action would be influenced by one own perceived status (membership) within a
community. Based on this theory, Chiu et al. (2015) reported that social identity (driven by
perceived external prestige and perceived community distinctiveness) has positive effect on
community participation. In addition to social identity, social influence theory depicts how
ones attitudes and actions would be changed by social influence which can be realised by
compliance, internalisation (IN) and identification. Analysis results suggested that IN was
found significant while both compliance and identification were deemed as insignificant,
which again contracted the theory (Cheung et al., 2011). Moreover, social capital theory has
been applied to address how social structures and relationships among members would
impact the voluntary community participation (Son et al.,2016). Conventionally, socialcapital
has three dimensions, i.e. structural, relationship and cognitive. Yang and Li (2016) explored

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